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How good must their training pipelines be? Releasing publicly and at this rate has made them very efficient.
by genxy 5mo ago
How good must their training pipelines be? Releasing publicly and at this rate has made them very efficient.
- sleepyeldrazi 5mo agoFinetuning takes little resources, the base model training is the slow and expensive part. Architecturally 3.5 models are identical to their 3.6 counterparts, that is why there is a consensus that those are probably finetunes and not re-trained from scratch, like you will se many people publish their own on huggingface.
- genxy 5mo agoUnderstood, but look at their larger cadence over the years and the breadth of models. They are clearly not all finetunes. Meta for all its billions, doesn't have anything comparable.
- Computer0 5mo agocompetent leadership goes a long way
- throwa356262 5mo agoThat was true up to Qwen 3.5, everything after that is made by the same people that made Gemini 3.1 suck
- bachmeier 5mo ago> Meta for all its billions, doesn't have anything comparable. Maybe nothing released to the public. I don't know that all of their models are public. I think all they really care about is that they aren't relying on one or two cloud providers for a critical piece of their infrastructure.
- fgonzag 5mo agoIn the china AI scene, there seem to be two separate types of companies. Companies or labs like deepseek that produce less but larger and more innovative models, so seem to be more research oriented. then there are companies like z.ai (GLM), Minimax, and Qwen which focus more on commercializing the AI and so produce far more versions, but with far less improvements between them (usually fine tunes) Commercial providers like anthropic probably do the same thing, maybe even without labeling it like a different version if the model is similiar enough.